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Murphy, Daniel L.; Beretvas, S. Natasha; Pituch, Keenan A. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a…
Descriptors: Sample Size, Simulation, Factor Structure, Statistical Analysis
Jones-Farmer, L. Allison – Structural Equation Modeling: A Multidisciplinary Journal, 2010
When comparing latent variables among groups, it is important to first establish the equivalence or invariance of the measurement model across groups. Confirmatory factor analysis (CFA) is a commonly used methodological approach to examine measurement equivalence/invariance (ME/I). Within the CFA framework, the chi-square goodness-of-fit test and…
Descriptors: Factor Structure, Factor Analysis, Evaluation Research, Goodness of Fit
French, Brian F.; Finch, W. Holmes – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Multigroup confirmatory factor analysis (MCFA) is a popular method for the examination of measurement invariance and specifically, factor invariance. Recent research has begun to focus on using MCFA to detect invariance for test items. MCFA requires certain parameters (e.g., factor loadings) to be constrained for model identification, which are…
Descriptors: Test Items, Simulation, Factor Structure, Factor Analysis
Hayashi, Kentaro; Yuan, Ke-Hai – Structural Equation Modeling: A Multidisciplinary Journal, 2003
Bayesian factor analysis (BFA) assumes the normal distribution of the current sample conditional on the parameters. Practical data in social and behavioral sciences typically have significant skewness and kurtosis. If the normality assumption is not attainable, the posterior analysis will be inaccurate, although the BFA depends less on the current…
Descriptors: Bayesian Statistics, Factor Analysis, Factor Structure
Quilty, Lena C.; Oakman, Jonathan M.; Risko, Evan – Structural Equation Modeling: A Multidisciplinary Journal, 2006
Investigators of personality assessment are becoming aware that using positively and negatively worded items in questionnaires to prevent acquiescence may negatively impact construct validity. The Rosenberg Self-Esteem Scale (RSES) has demonstrated a bifactorial structure typically proposed to result from these method effects. Recent work suggests…
Descriptors: Measures (Individuals), Personality Traits, Test Validity, Personality Assessment
Kim, Sooyeon; Hagtvet, Knut A. – Structural Equation Modeling: A Multidisciplinary Journal, 2003
This study focused on misspecifications in composing parcels to represent a latent construct. Two measurement design factors, item reliability and intercorrelations among parcels, defined 12 true unidimensional parcel models. Deviations from the true model were examined via a 2-facet measurement model in which items and parcels represented the 2…
Descriptors: Simulation, Factor Structure, Measurement Techniques, Goodness of Fit